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20222026
most citedAn AI-powered Public Health Automated Kiosk System for Personalized Care: An Experimental Pilot Study

1 citations · 2 across the 16 of their papers we have counts for

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physics.med-ph2025

Towards Interpretable AI in Personalized Medicine: A Radiological-Biological Radiomics Dictionary Connecting Semantic Lung-RADS and imaging Radiomics Features; Dictionary LC 1.0

Ali Fathi Jouzdani, Shahram Taeb, Mehdi Maghsudi +3

Lung cancer remains the leading cause of cancer-related mortality worldwide, with survival strongly dependent on early detection. Standard-dose computed tomography (CT) screening u…

physics.med-ph2025

PySERA: Open-Source Standardized Python Library for Automated, Scalable, and Reproducible Handcrafted and Deep Radiomics

Mohammad R. Salmanpour, Amir Hossein Pouria, Sirwan Barichin +5

Radiomics enables the extraction of quantitative biomarkers from medical images for precision modeling, but reproducibility and scalability remain limited due to heterogeneous soft…

physics.med-ph2025

Semi-Supervised Radiomics for Glioblastoma IDH Mutation: Limited Labels, Data Sensitivity, and SHAP Interpretation

Amir Hossein Pouria, Shahram Taeb, Somayeh Sadat Mehrnia +4

Glioblastoma (GBM) is an aggressive brain tumor in which IDH mutation status is a key prognostic biomarker, but traditional testing requires invasive biopsies, emphasizing the need…

physics.med-ph2025

Handcrafted vs. Deep Radiomics vs. Fusion vs. Deep Learning: A Comprehensive Review of Machine Learning -Based Cancer Outcome Prediction in PET and SPECT Imaging

Mohammad R. Salmanpour, Somayeh Sadat Mehrnia, Sajad Jabarzadeh Ghandilu +7

Machine learning (ML), including deep learning (DL) and radiomics-based methods, is increasingly used for cancer outcome prediction with PET and SPECT imaging. However, the compara…

physics.med-ph2025

Robust Semi-Supervised CT Radiomics for Lung Cancer Prognosis: Cost-Effective Learning with Limited Labels and SHAP Interpretation

Mohammad R. Salmanpour, Amir Hossein Pouria, Sonia Falahati +7

Background: CT imaging is vital for lung cancer management, offering detailed visualization for AI-based prognosis. However, supervised learning SL models require large labeled dat…

physics.med-ph2025

Censor-Aware Semi-Supervised Survival Time Prediction in Lung Cancer Using Clinical and Radiomics Features

Arman Gorji, Ali Fathi Jouzdani, Nima Sanati +3

Objectives: Lung cancer poses a significant global health challenge, necessitating improved prognostic methods for personalized treatment. This study introduces a censor-aware semi…

physics.med-ph2024

Biological and Radiological Dictionary of Radiomics Features: Addressing Understandable AI Issues in Personalized Prostate Cancer; Dictionary Version PM1.0

Mohammad R. Salmanpour, Sajad Amiri, Sara Gharibi +5

We investigate the connection between visual semantic features defined in PI-RADS and associated risk factors, moving beyond abnormal imaging findings, establishing a shared framew…